R Notebook

library(data.table)

Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
data.table 1.14.8 using 1 threads (see ?getDTthreads).  Latest news: r-datatable.com
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This installation of data.table has not detected OpenMP support. It should still work but in single-threaded mode.
This is a Mac. Please read https://mac.r-project.org/openmp/. Please engage with Apple and ask them for support. Check r-datatable.com for updates, and our Mac instructions here: https://github.com/Rdatatable/data.table/wiki/Installation. After several years of many reports of installation problems on Mac, it's time to gingerly point out that there have been no similar problems on Windows or Linux.
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library(tidyr)

#read the data

# Data of Wave 5


WV5_data <- readRDS("/Users/cristinacandido/Documents/Github/risk_wvs/data/WVS/F00007944-WV5_Data_R_v20180912.rds")


# Convert WV5_data-object in data.frame 
WV5_data_df <- as.data.frame(WV5_data)

# show first five columns
head(WV5_data_df[, 1:5])

``

library(dplyr)

#rename the variables
WV5_data <- WV5_data_df %>%
  rename(risk_and_adventure = V86, sex = V235, age = V237, country = V2)
WV5_data

#select only the variables of interest
WV5_data <- WV5_data %>%
  select(risk_and_adventure, sex, age, country)
WV5_data

#exlcusion of participants with no info about risk, sex, age, employment, merital status and children 
WV5_data_df = subset(WV5_data, risk_and_adventure > 0 & sex > 0 & age >0)

#decode the country names 
countrynames = read.csv("/Users/cristinacandido/Documents/Github/risk_wvs/data/WVS/countrynames.txt", header=FALSE,as.is=TRUE)
colnames(countrynames) = c("code", "name")
WV5_data$country_lab = countrynames$name [match(WV5_data$country, countrynames$code)]
table(WV5_data$country_lab)

            Andorra           Argentina           Australia              Brazil            Bulgaria        Burkina Faso              Canada               Chile 
               1003                1002                1421                1500                1001                1534                2164                1000 
              China            Colombia          Cyprus (G)               Egypt            Ethiopia             Finland              France             Georgia 
               1991                3025                1050                3051                1500                1014                1001                1500 
            Germany               Ghana       Great Britain           Guatemala           Hong Kong             Hungary               India           Indonesia 
               2064                1534                1041                1000                1252                1007                2001                2015 
               Iran                Iraq               Italy               Japan              Jordan            Malaysia                Mali              Mexico 
               2667                2701                1012                1096                1200                1201                1534                1560 
            Moldova             Morocco         Netherlands         New Zealand              Norway                Peru              Poland             Romania 
               1046                1200                1050                 954                1025                1500                1000                1776 
             Russia              Rwanda            Slovenia        South Africa         South Korea               Spain              Sweden         Switzerland 
               2033                1507                1037                2988                1200                1200                1003                1241 
             Taiwan            Thailand Trinidad and Tobago              Turkey             Ukraine       United States             Uruguay            Viet Nam 
               1227                1534                1002                1346                1000                1249                1000                1495 
             Zambia 
               1500 

WV5_data

NA
NA

WV6_data <- load("/Users/cristinacandido/Documents/Github/risk_wvs/data/WVS/WV6_Data_R_v20201117.rdata") 
WV6_data <- WV6_Data_R_v20201117 
print(WV6_data)

WV6_data <- WV6_data %>%
  rename(risk_and_adventure = V76, sex = V240, age = V242, education = V237, country = V2)


#select only the variables of interest
WV6_data <- WV6_data %>%
  select(risk_and_adventure, sex, age, country)
WV6_data

NA

countrynames = read.csv("/Users/cristinacandido/Documents/Github/risk_wvs/data/WVS/countrynames.txt", header=FALSE,as.is=TRUE)
colnames(countrynames) = c("code", "name")
WV6_data$country_lab = countrynames$name [match(WV6_data$country, countrynames$code)]
table(WV6_data$country_lab)

            Algeria           Argentina             Armenia           Australia          Azerbaijan             Belarus              Brazil               Chile 
               1200                1030                1100                1477                1002                1535                1486                1000 
              China            Colombia          Cyprus (G)             Ecuador               Egypt             Estonia             Georgia             Germany 
               2300                1512                1000                1202                1523                1533                1202                2046 
              Ghana               Haiti           Hong Kong               India                Iraq               Japan              Jordan          Kazakhstan 
               1552                1996                1000                4078                1200                2443                1200                1500 
             Kuwait          Kyrgyzstan             Lebanon               Libya            Malaysia              Mexico             Morocco         Netherlands 
               1303                1500                1200                2131                1300                2000                1200                1902 
        New Zealand             Nigeria            Pakistan           Palestine                Peru         Philippines              Poland               Qatar 
                841                1759                1200                1000                1210                1200                 966                1060 
            Romania              Russia              Rwanda           Singapore            Slovenia        South Africa         South Korea               Spain 
               1503                2500                1527                1972                1069                3531                1200                1189 
             Sweden              Taiwan            Thailand Trinidad and Tobago             Tunisia              Turkey             Ukraine       United States 
               1206                1238                1200                 999                1205                1605                1500                2232 
            Uruguay          Uzbekistan               Yemen            Zimbabwe 
               1000                1500                1000                1500 

WV6_data

WV6_data = subset(WV6_data, risk_and_adventure > 0 & sex > 0 & age >0)
data = rbind(WV5_data, WV6_data)
data